Search Results (40)

This study addresses the challenge of drilling film-cooling holes in the turbine blades of aircraft engines. Titanium alloy TC4 was selected as the experimental material. The laser-drilling process was simulated with ANSYS to determine optimal parameters, which were subsequently applied in machining trials. An impact-drilling method was then used to evaluate how pulse width, pulse energy, and pulse count affect micro-hole entrance and exit diameters, taper, and roundness. Simulations revealed that pulse energy and pulse count predominantly govern entrance and exit diameters, whereas pulse count and pulse width exert a stronger influence on taper. Experiments confirmed that entrance and exit diameters increased as pulse energy rose from 2.0 J to 2.8 J; taper increased as pulse width widened from 0.6 ms to 1.4 ms; and entrance diameter, exit diameter, and taper all grew as pulse count rose from 40 to 60. Pulse width and pulse count also significantly affected hole roundness. Full article

This study evaluates the applicability and accuracy of coarse-grain modeling (CGM) in discrete-element method (DEM)–based simulations, focusing on particle-mixing efficiency in five representative industrial mixers: the tumbling V mixer, ribbon-blade mixer, paddle-blade mixer, vertical-blade mixer, and conical-screw mixer. Although the DEM is widely employed for particulate system simulations, the high computational cost associated with fine particles significantly hinders large-scale applications. CGM addresses these issues by scaling up particle sizes, thereby reducing particle counts and allowing longer simulation timesteps. We utilized the Lacey mixing index (LMI) as a statistical measure to quantitatively assess mixing uniformity across various CGM scaling factors. Based on the results, CGM significantly reduced computational time (by over 90% in certain cases) while preserving acceptable accuracy levels in terms of LMI values. The mixing behaviors remained consistent under various CGM conditions, based on both visually inspected particle distributions and the temporal LMI trends. Although minor deviations occurred in early-stage mixing, these discrepancies diminished with time, with the final LMI errors remaining below 5% in most scenarios. These findings indicate that CGM effectively enhances computational efficiency in DEM simulations without significantly compromising physical accuracy. This research provides practical guidelines for optimizing industrial-scale particle-mixing processes and conducting computationally feasible, scalable, and reliable DEM simulations. Full article

Given that cryogenic pumps on liquefied natural gas (LNG) carriers are prone to cavitation under complex operating conditions, this paper examines the inducer of an LNG centrifugal pump to uncover how the inducer geometry affects both the cavitation behavior and internal flow-induced excitation at −163 °C. Through detailed numerical simulations, we evaluate the cavitation performance and flow excitation characteristics across a range of inducer designs, systematically varying the blade count, inlet and outlet angles, and blade wrap angle. Our results show that reducing the number of blades, together with properly optimized inlet/outlet and wrap angles, significantly enhances the cavitation resistance. These findings provide a solid theoretical basis and practical guidance for the engineering optimization of LNG ship pumps. Full article

Performance degradation of wind turbine blades often stems from geometric asymmetry induced by damage. Existing methods for assessing damage face challenges in balancing accuracy and efficiency due to their limited ability to capture fine-grained geometric asymmetries associated with multi-scale damage under complex background interference. To address this, based on the high-speed detection model YOLOv10-N, this paper proposes a novel detection model named MMC-YOLO. First, the Multi-Scale Perception Gated Convolution (MSGConv) Module was designed, which constructs a full-scale receptive field through multi-branch fusion and channel rearrangement to enhance the extraction of geometric asymmetry features. Second, the Multi-Scale Enhanced Feature Pyramid Network (MSEFPN) was developed, integrating dynamic path aggregation and an SENetv2 attention mechanism to suppress background interference and amplify damage response. Finally, the Channel-Compensated Filtering (CCF) module was constructed to preserve critical channel information using a dynamic buffering mechanism. Evaluated on a dataset of 4818 wind turbine blade damage images, MMC-YOLO achieves an 82.4% mAP [0.5:0.95], representing a 4.4% improvement over the baseline YOLOv10-N model, and a 91.1% recall rate, an 8.7% increase, while maintaining a lightweight parameter count of 4.2 million. This framework significantly enhances geometric asymmetry defect detection accuracy while ensuring real-time performance, meeting engineering requirements for high efficiency and precision. Full article

This study investigates the performance of B-series marine propellers enhanced through geometric modifications, namely face camber ratio (FCR) and cupping percentage modifications, using a machine learning (ML)-driven optimization framework. A large dataset of over 7000 open-water propeller configurations is curated, incorporating variations in blade number, expanded area ratio (EAR), pitch-to-diameter ratio (P/D), FCR, and cupping percentage. A multi-layer artificial neural network (ANN) is trained to predict thrust, torque, and open-water efficiency (η_o) with a high coefficient of determination (R²), greater than 0.9999. The ANN is integrated into an optimization algorithm to identify optimal propeller designs for the KRISO Container Ship (KCS) using empirical constraints for cavitation and tip speed. Unlike prior studies that rely on boundary element method (BEM)-ML hybrids or multi-fidelity simulations, this study introduces a geometry-coupled analysis of FCR and cupping—parameters often treated independently—and applies empirical cavitation and acoustic (tip speed) limits to guide the design process. The results indicate that incorporating 1.0–1.5% cupping leads to a significant improvement in efficiency, up to 9.3% above the reference propeller, while maintaining cavitation safety margins and acoustic limits. Conversely, designs with non-zero FCR values (0.5–1.5%) show a modest efficiency penalty (up to 4.3%), although some configurations remain competitive when compensated by higher EAR, P/D, or blade count. The study confirms that the combination of cupping with optimized geometric parameters yields high-efficiency, cavitation-safe propellers. Furthermore, the ML-based framework demonstrates excellent potential for rapid, accurate, and scalable propeller design optimization that meets both performance and regulatory constraints. Full article

The intentional yaw offset of wind turbines has shown potential to redirect wakes, enhancing overall plant power production, but it may increase fatigue loading on turbine components. This study analyzed fatigue loads on the NREL 5 MW reference wind turbine under varying yaw offsets using blade element momentum theory, dynamic blade element momentum, and the converging Lagrange filaments vortex method, all implemented in OpenFAST. Simulations employed yaw angles from −40° to 40°, with turbulent inflow generated by TurbSim, an OpenFAST tool for realistic wind conditions. Fatigue loads were calculated according to IEC 61400-1 design load case 1.2 standards, using thirty simulations per yaw angle across five wind speed bins. Damage equivalent load was evaluated via rainflow counting, Miner’s rule, and Goodman correction. Results showed that the free vortex method, by modeling unsteady aerodynamic forces, yielded distinct differences in damage equivalent load compared to the blade element method in yawed conditions. The free vortex method predicted lower damage equivalent load for the low-speed shaft bending moment at negative yaw offsets, attributed to its improved handling of unsteady effects that reduce load variations. Conversely, for yaw offsets above 20°, the free vortex method indicated higher damage equivalent for low-speed shaft torque, reflecting its accurate capture of dynamic inflow and unsteady loading. These findings highlight the critical role of unsteady aerodynamics in fatigue load predictions and demonstrate the free vortex method’s value within OpenFAST for realistic damage equivalent load estimates in yawed turbines. The results emphasize the need to incorporate unsteady aerodynamic models like the free vortex method to accurately assess yaw offset impacts on wind turbine component fatigue. Full article

Fusarium wilt (FW), induced by Fusarium oxysporum, poses a significant threat to global tomato (Solanum lycopersicum L.) production, leading to substantial yield reduction. This study investigated the anatomical and ultrastructural responses of tomato leaves to FW infection and assessed the efficacy of salicylic acid (SA), humic acid (HA), and zinc oxide nanoparticles (ZnO-NPs) as control and inducer agents. FW infection resulted in notable structural alterations, including decreased leaf blade and mesophyll thickness and increased Adaxial epidermal cell wall thickness, thereby disrupting the leaf structure. Also, it caused severe chloroplast damage, such as membrane detachment and a reduced count of starch granules, which could impair photosynthetic efficiency. The different treatments exhibited significant effectiveness in reversing these adverse effects, leading to increased thickness of the leaf blade, mesophyll, palisade, and spongy tissues and enhanced structural integrity. Furthermore, ultrastructural improvements included activated mitochondria, compact chloroplasts with increased numbers, and proliferation of plastoglobuli, indicating adaptive metabolic changes. Principal component analysis (PCA-biplot) highlighted the significant parameters distinguishing treatment groups, providing insights into trait-based differentiation. This study concluded the potential of SA, HA, and ZnO-NPs as sustainable solutions for managing Fusarium wilt and enhancing tomato plant resilience, thereby contributing to improved agricultural practices and food security. Full article

In firefighting operations, the efficiency of centrifugal fire pumps is crucial for effective fire suppression. Designs aiming for lower shaft power enhance not only the pump’s energy efficiency and reliability but also lead to a reduction in size and weight. This research targets a single-stage centrifugal fire pump with a specific speed of 44.5, employing numerical simulations alongside orthogonal experiments to primarily focus on reducing shaft power. Based on a prototype, an L₁₆(4⁴) orthogonal experiment was conducted on four critical parameters: blade outlet angle, wrap angle, outlet width, and blade count. The study analyzed the impact of these parameters on pump performance, clarifying their influence on the hydraulic performance and proposing an optimal power-efficiency scheme. The optimized design successfully reduced the motor power from 18.5 kW to 15 kW, improved the impeller’s internal flow, minimized flow losses, and effectively managed the hump phenomenon. Operating at 1.5 Q_n, the optimized pump’s power decreased by 2.67 kW, meeting head requirements while boosting efficiency, reducing resonance frequency, and lowering the pressure amplitude at the tongue. The optimized pump’s blade frequency distribution was more regular than the original, with the first-order mode’s average deformation decreasing from 3.6 mm to 3.3 mm, and average entropy production at rated flow dropping from 424.118 [W·m⁻³·K⁻¹] to 384.957 [W·m⁻³·K⁻¹]. These outcomes offer theoretical insights and practical guidance for designing low-shaft-power single-stage centrifugal fire pumps, significantly impacting energy efficiency and operational costs. Full article

Blowers, essential for aerator operation, are pivotal mechanical devices that induce airflow through an impeller. Extensive research has explored impeller geometrical parameters, such as size, angle, and blade count. However, limited attention has been paid to the synergic effect of optimizing the bell mouth of the blower inlet and the nose cone of the impeller eye. This study utilized computational fluid dynamics (CFDs) to analyze the impact of the bell mouth and nose cone on the blower through a geometric case study and evaluate the synergy between these components. A bell mouth decreases the wake by 91.76%, and a nose cone decreases the stagnation at the impeller eye and expands the effective impeller area by 76.29%. Moreover, this study demonstrated a significant synergistic effect between the bell mouth and nose cone, which reduced the head loss by 81.4% compared with the base model. This study presents a simple and effective method to improve blower efficiency and reduce power consumption by applying aerodynamically designed bell mouths and nose cones to blowers. Full article

This study presents a comprehensive investigation into multi-directional fatigue damage characteristics of fixed offshore wind turbine tower roots through comparative analysis using FAST (3.5.0) and Bladed (4.3) software platforms. The research methodology encompasses three principal phases: First, a stochastic wind field model was developed through statistical analysis of historical wind speed measurements, achieving superior correlation (R² = 0.983) in goodness-of-fit tests. Subsequently, the rain flow counting technique was employed to characterize equivalent cyclic load spectra. Building upon these foundations, an integrated predictive fatigue life evaluation framework was formulated by synergistically combining S–N curve principles with Palmgren–Miner’s linear cumulative damage theory. The methodology was further validated through cross-platform verification with Bladed software, revealing only a 7.4% deviation in predicted fatigue lives between the two computational models, confirming the technical feasibility of the proposed simplified model. Full article

This study explores the implications of the number of blades on the performance of both open and shrouded rotors. By conducting a thorough experimental analysis at a fixed solidity ratio, this research seeks to enhance our understanding of rotor dynamics and efficiency. Two-, three-, four-, and five-bladed rotors were designed and manufactured to have the same solidity ratio. This leads to smaller chord distribution values for higher blade numbers. The experimental analysis aims to quantify the effects of the number of blades and provides a comparative analysis of performance differences between the two rotor configurations (shrouded and open). For the open rotor, results indicate that increasing the number of blades has a minimal impact on overall performance. This is due to the decrease in the tip loss factor being counterbalanced by a decline in efficiency caused by the two-dimensional airfoil performance, which results from a smaller chord and a lower Reynolds number. In contrast, the shrouded rotor exhibits a noticeable performance decay with an increased blade count. Since tip loss is inherently absent in shrouded designs, the decline is primarily attributed to the two-dimensional airfoil performance. This decay occurs while maintaining a constant solidity ratio, highlighting the significant effect of blade count on shrouded rotor efficiency, thereby contributing to the optimization of rotor design in various engineering applications. Full article

Dual-mode propellers, as propulsion and turbine devices, have found widespread application in renewable energy systems for marine vehicles, particularly in sailing boats and yachts. However, the existing dual-mode propellers in these contexts are typically chosen in an off-the-shelf manner, indicating a lack of hydrodynamic optimisation to enhance both the propulsion and energy generation efficiency in the same rotor. To address this limitation and furnish scientific validation of the design of a dual-mode propeller turbine rotor optimised to achieve a balanced performance in both propulsion and energy generation, rigorous experimentation was conducted using specialised software, Rotorysics 2019, and a case study vessel, the Princess Royale. Utilising prior experimental data for this propeller turbine, code validation was undertaken to ensure accurate prediction of the effects of the pitch, blade count and expanded area ratio on the performance in both modes. With the intention of achieving optimal power generation and propulsion efficiencies in conjunction with a single rotor, the findings reveal that the optimised fixed-pitch propeller exhibits dual functionality. They serve as both propulsion and tidal/current turbines with balanced efficiency. They are particularly suitable for low-speed vessels such as yachts anchored in currents or for sailboats utilising a propeller as a towed turbine. Through thorough testing and analysis, the concept of a dual-mode propeller turbine was feasible. Analysing them separately, in terms of the propulsion, the best geometry found through numerous tests of different expanded area ratios, blade number, pitch and speed was the 3-blade, 0.6 pitch ratio, which achieved a propulsive efficiency of 54.33% (0.5433204) and a power coefficient of 0.291843. Conversely, if the focus was on power generation while maintaining excellent propulsive efficiency, the optimal geometry would be the 5-blade, 0.6 pitch ratio, which offers a power coefficient of 0.348402 and a propulsive efficiency of 48.55% (0.48547). However, when using both power generation and propulsion as the criteria, the 5-blade, 0.6 pitch ratio, with an EAR of 0.387142, is superior, with balanced optimisation, offering a propulsive efficiency of 52.53% (0.52527) and a power coefficient of 0.319718. As expected, this encompasses a higher blade number for increased power generation efficiency and a higher pitch ratio for increased propulsive efficiency. Full article

The balance between accuracy and computational complexity is currently a focal point of research in dynamical system modeling. From the perspective of model reduction, this paper addresses the mode selection strategy in Dynamic Mode Decomposition (DMD) by integrating an embedded fractal theory based on fractal dimension (FD). The existing model selection methods lack interpretability and exhibit arbitrariness in choosing mode dimension truncation levels. To address these issues, this paper analyzes the geometric features of modes for the dimensional characteristics of dynamical systems. By calculating the box counting dimension (BCD) of modes and the correlation dimension (CD) and embedding dimension (ED) of the original dynamical system, it achieves guidance on the importance ranking of modes and the truncation order of modes in DMD. To validate the practicality of this method, it is applied to the reduction applications on the reconstruction of the velocity field of cylinder wake flow and the force field of compressor blades. Theoretical results demonstrate that the proposed selection technique can effectively characterize the primary dynamic features of the original dynamical systems. By employing a loss function to measure the accuracy of the reconstruction models, the computed results show that the overall errors of the reconstruction models are below 5%. These results indicate that this method, based on fractal theory, ensures the model’s accuracy and significantly reduces the complexity of subsequent computations, exhibiting strong interpretability and practicality. Full article

The wear phenomenon that occurs on the blades during operation has a significant impact on the fatigue life of the blades. To address the issue of fatigue life assessment for turbine runner blades subjected to increased dynamic stress due to sediment wear, taking a specific high-head hydropower unit’s mixed-flow turbine as the research subject, a hydraulic model of the turbine was established. The wear zones of the runner blades are determined based on the distribution of the flow field’s velocity and the sediment volume fraction. According to the wear rate formula for runner blade material, the amount of wear on the blades is determined, and the dynamic stress data for the dangerous areas of the blades under different degrees of wear are calculated using a unidirectional fluid–structure coupling method. The load spectrum of the time–stress history data for the dangerous area at different levels of wear was compiled using the rain-flow counting statistical method. The operating time ratios for the flood season and the non-flood season are combined. Based on the fatigue cumulative damage theory, the total fatigue damage at the maximum stress part of the runner blade was calculated for different stages of wear, providing a reference for the life calculation of mixed-flow hydraulic turbines. Full article

Wind turbine blades are the core components responsible for efficient wind energy conversion and ensuring stability. To address challenges in wind turbine blade damage detection using image processing techniques such as complex image backgrounds, decreased detection performance due to high image resolution, prolonged inference time, and insufficient recognition accuracy, this study introduces an enhanced wind turbine blade damage detection model named WTDB-YOLOv8. Firstly, by incorporating the GhostCBS and DFSB-C2f modules, the aim is to reduce the number of model parameters while enhancing feature extraction capability. Secondly, by integrating the MHSA-C2f module, which incorporates a multi-head self-attention mechanism, the focus on global information is enabled, thereby mitigating irrelevant background interference and reducing the impact of complex backgrounds on damage detection. Lastly, adopting the Mini-BiFPN structure improves the retention of features for small target objects in shallow networks and reinforces the propagation of these features in deep networks, thereby enhancing the detection accuracy of small target damage and reducing false negative rates. Through training and testing on the Wind Turbine Blade Damage Dataset (WTBDD), the WTDB-YOLOv8 model achieves an average precision of 98.3%, representing a 2.2 percentage point improvement over the original YOLOv8 model. Particularly noteworthy is the increase in precision from 93.1% to 97.9% in small target damage detection. Moreover, the total parameter count of the model decreases from 3.22 million in YOLOv8 to 1.99 million, marking a reduction of 38.2%. Therefore, the WTDB-YOLOv8 model not only enhances the detection performance and efficiency of wind turbine blade damage but also significantly reduces the model parameter count, showcasing its practical advantages in engineering applications. Full article